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Posted to commits@spark.apache.org by sr...@apache.org on 2017/10/31 08:20:30 UTC
spark git commit: [SPARK-22399][ML] update the location of reference
paper
Repository: spark
Updated Branches:
refs/heads/master 1ff41d869 -> aa6db57e3
[SPARK-22399][ML] update the location of reference paper
## What changes were proposed in this pull request?
Update the url of reference paper.
## How was this patch tested?
It is comments, so nothing tested.
Author: bomeng <bm...@us.ibm.com>
Closes #19614 from bomeng/22399.
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/aa6db57e
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/aa6db57e
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/aa6db57e
Branch: refs/heads/master
Commit: aa6db57e39d4931658089d9237dbf2a29acfe5ed
Parents: 1ff41d8
Author: bomeng <bm...@us.ibm.com>
Authored: Tue Oct 31 08:20:23 2017 +0000
Committer: Sean Owen <so...@cloudera.com>
Committed: Tue Oct 31 08:20:23 2017 +0000
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docs/mllib-clustering.md | 2 +-
.../spark/examples/mllib/PowerIterationClusteringExample.scala | 3 ++-
.../spark/mllib/clustering/PowerIterationClustering.scala | 6 +++---
python/pyspark/mllib/clustering.py | 2 +-
4 files changed, 7 insertions(+), 6 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/aa6db57e/docs/mllib-clustering.md
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diff --git a/docs/mllib-clustering.md b/docs/mllib-clustering.md
index 8990e95..df2be92 100644
--- a/docs/mllib-clustering.md
+++ b/docs/mllib-clustering.md
@@ -134,7 +134,7 @@ Refer to the [`GaussianMixture` Python docs](api/python/pyspark.mllib.html#pyspa
Power iteration clustering (PIC) is a scalable and efficient algorithm for clustering vertices of a
graph given pairwise similarities as edge properties,
-described in [Lin and Cohen, Power Iteration Clustering](http://www.icml2010.org/papers/387.pdf).
+described in [Lin and Cohen, Power Iteration Clustering](http://www.cs.cmu.edu/~frank/papers/icml2010-pic-final.pdf).
It computes a pseudo-eigenvector of the normalized affinity matrix of the graph via
[power iteration](http://en.wikipedia.org/wiki/Power_iteration) and uses it to cluster vertices.
`spark.mllib` includes an implementation of PIC using GraphX as its backend.
http://git-wip-us.apache.org/repos/asf/spark/blob/aa6db57e/examples/src/main/scala/org/apache/spark/examples/mllib/PowerIterationClusteringExample.scala
----------------------------------------------------------------------
diff --git a/examples/src/main/scala/org/apache/spark/examples/mllib/PowerIterationClusteringExample.scala b/examples/src/main/scala/org/apache/spark/examples/mllib/PowerIterationClusteringExample.scala
index 986496c..6560325 100644
--- a/examples/src/main/scala/org/apache/spark/examples/mllib/PowerIterationClusteringExample.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/mllib/PowerIterationClusteringExample.scala
@@ -28,7 +28,8 @@ import org.apache.spark.mllib.clustering.PowerIterationClustering
import org.apache.spark.rdd.RDD
/**
- * An example Power Iteration Clustering http://www.icml2010.org/papers/387.pdf app.
+ * An example Power Iteration Clustering app.
+ * http://www.cs.cmu.edu/~frank/papers/icml2010-pic-final.pdf
* Takes an input of K concentric circles and the number of points in the innermost circle.
* The output should be K clusters - each cluster containing precisely the points associated
* with each of the input circles.
http://git-wip-us.apache.org/repos/asf/spark/blob/aa6db57e/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
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diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
index b2437b8..9444f29 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/PowerIterationClustering.scala
@@ -103,9 +103,9 @@ object PowerIterationClusteringModel extends Loader[PowerIterationClusteringMode
/**
* Power Iteration Clustering (PIC), a scalable graph clustering algorithm developed by
- * <a href="http://www.icml2010.org/papers/387.pdf">Lin and Cohen</a>. From the abstract: PIC finds
- * a very low-dimensional embedding of a dataset using truncated power iteration on a normalized
- * pair-wise similarity matrix of the data.
+ * <a href="http://www.cs.cmu.edu/~frank/papers/icml2010-pic-final.pdf">Lin and Cohen</a>.
+ * From the abstract: PIC finds a very low-dimensional embedding of a dataset using
+ * truncated power iteration on a normalized pair-wise similarity matrix of the data.
*
* @param k Number of clusters.
* @param maxIterations Maximum number of iterations of the PIC algorithm.
http://git-wip-us.apache.org/repos/asf/spark/blob/aa6db57e/python/pyspark/mllib/clustering.py
----------------------------------------------------------------------
diff --git a/python/pyspark/mllib/clustering.py b/python/pyspark/mllib/clustering.py
index 91123ac..bb687a7 100644
--- a/python/pyspark/mllib/clustering.py
+++ b/python/pyspark/mllib/clustering.py
@@ -636,7 +636,7 @@ class PowerIterationClusteringModel(JavaModelWrapper, JavaSaveable, JavaLoader):
class PowerIterationClustering(object):
"""
Power Iteration Clustering (PIC), a scalable graph clustering algorithm
- developed by [[http://www.icml2010.org/papers/387.pdf Lin and Cohen]].
+ developed by [[http://www.cs.cmu.edu/~frank/papers/icml2010-pic-final.pdf Lin and Cohen]].
From the abstract: PIC finds a very low-dimensional embedding of a
dataset using truncated power iteration on a normalized pair-wise
similarity matrix of the data.
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